When Bounce Rate, Browse Rate (PPV), and Time-on-Site Are Useful Metrics... and When They Aren't - Whiteboard&nbspFriday

The author's views are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.

When is it right to use metrics like bounce rate, pages per visit, and time on site? When are you better off ignoring them? There are endless opinions on whether these kinds of metrics are valuable or not, and as you might suspect, the answer is found in the shades of grey. Learn what Rand has to say about the great metrics debate in today's episode of Whiteboard Friday.

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Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we're chatting about times at which bounce rate, browse rate, which is pages per visit, and time on site are terrible metrics and when they're actually quite useful metrics.

This happens quite a bit. I see in the digital marketing world people talking about these metrics as though they are either dirty-scum, bottom-of-the-barrel metrics that no one should pay any attention to, or that they are these lofty, perfect metrics that are what we should be optimizing for. Neither of those is really accurate. As is often the case, the truth usually lies somewhere in between.

So, first off, some credit to Wil Reynolds, who brought this up during a discussion that I had with him at Siege Media's offices, an interview that Ross Hudgens put together with us, and Sayf Sharif from Seer Interactive, their Director of Analytics, who left an awesome comment about this discussion on the LinkedIn post of that video. We'll link to those in this Whiteboard Friday.

So Sayf and Wil were both basically arguing that these are kind of crap metrics. We don't trust them. We don't use them a lot. I think, a lot of the time, that makes sense.

Instances when these metrics aren't useful

Here's when these metrics, that bounce rate, pages per visit, and time on site kind of suck.

1. When they're used instead of conversion actions to represent "success"

So they suck when you use them instead of conversion actions. So a conversion is someone took an action that I wanted on my website. They filled in a form. They purchased a product. They put in their credit card. Whatever it is, they got to a page that I wanted them to get to.

Bounce rate is basically the average percent of people who landed on a page and then left your website, not to continue on any other page on that site after visiting that page.

Pages per visit is essentially exactly what it sounds like, the average number of pages per visit for people who landed on that particular page. So people who came in through one of these pages, how many pages did they visit on my site.

Then time on site is essentially a very raw and rough metric. If I leave my computer to use the restroom or I basically switch to another tab or close my browser, it's not necessarily the case that time on site ends right then. So this metric has a lot of imperfections. Now, averaged over time, it can still be directionally interesting.

But when you use these instead of conversion actions, which is what we all should be optimizing for ultimately, you can definitely get into some suckage with these metrics.

2. When they're compared against non-relevant "competitors" and other sites

When you compare them against non-relevant competitors, so when you compare, for example, a product-focused, purchase-focused site against a media-focused site, you're going to get big differences. First off, if your pages per visit look like a media site's pages per visit and you're product-focused, that is crazy. Either the media site is terrible or you're doing something absolutely amazing in terms of keeping people's attention and energy.

Time on site is a little bit misleading in this case too, because if you look at the time on site, again, of a media property or a news-focused, content-focused site versus one that's very e-commerce focused, you're going to get vastly different things. Amazon probably wants your time on site to be pretty small. Dell wants your time on site to be pretty small. Get through the purchase process, find the computer you want, buy it, get out of here. If you're taking 10 minutes to do that or 20 minutes to do that instead of 5, we've failed. We haven't provided a good enough experience to get you quickly through the purchase funnel. That can certainly be the case. So there can be warring priorities inside even one of these metrics.

3. When they're not considered over time or with traffic sources factored in

Third, you get some suckage when they are not considered over time or against the traffic sources that brought them in. For example, if someone visits a web page via a Twitter link, chances are really good, really, really good, especially on mobile, that they're going to have a high bounce rate, a low number of pages per visit, and a low time on site. That's just how Twitter behavior is. Facebook is quite similar.

Now, if they've come via a Google search, an informational Google search and they've clicked on an organic listing, you should see just the reverse. You should see a relatively good bounce rate. You should see a relatively good pages per visit, well, a relatively higher pages per visit, a relatively higher time on site.

Instances when these metrics are useful

1. When they're used as diagnostics for the conversion funnel

So there's complexity inside these metrics for sure. What we should be using them for, when these metrics are truly useful is when they are used as a diagnostic. So when you look at a conversion funnel and you see, okay, our conversion funnel looks like this, people come in through the homepage or through our blog or news sections, they eventually, we hope, make it to our product page, our pricing page, and our conversion page.

We have these metrics for all of these. When we make changes to some of these, significant changes, minor changes, we don't just look at how conversion performs. We also look at whether things like time on site shrank or whether people had fewer pages per visit or whether they had a higher bounce rate from some of these sections.

So perhaps, for example, we changed our pricing and we actually saw that people spent less time on the pricing page and had about the same number of pages per visit and about the same bounce rate from the pricing page. At the same time, we saw conversions dip a little bit.

Should we intuit that pricing negatively affected our conversion rate? Well, perhaps not. Perhaps we should look and see if there were other changes made or if our traffic sources were in there, because it looks like, given that bounce rate didn't increase, given that pages per visit didn't really change, given that time on site actually went down a little bit, it seems like people are making it just fine through the pricing page. They're making it just fine from this pricing page to the conversion page, so let's look at something else.

This is the type of diagnostics that you can do when you have metrics at these levels. If you've seen a dip in conversions or a rise, this is exactly the kind of dig into the data that smart, savvy digital marketers should and can be doing, and I think it's a powerful, useful tool to be able to form hypotheses based on what happens.

So again, another example, did we change this product page? We saw pages per visit shrink and time on site shrink. Did it affect conversion rate? If it didn't, but then we see that we're getting fewer engaged visitors, and so now we can't do as much retargeting and we're losing email signups, maybe this did have a negative effect and we should go back to the other one, even if conversion rate itself didn't seem to take a particular hit in this case.

2. When they're compared over time to see if internal changes or external forces shifted behavior

Second useful way to apply these metrics is compared over time to see if your internal changes or some external forces shifted behavior. For example, we can look at the engagement rate on the blog. The blog is tough to generate as a conversion event. We could maybe look at subscriptions, but in general, pages per visit is a nice one for the blog. It tells us whether people make it past the page they landed on and into deeper sections, stick around our site, check out what we do.

So if we see that it had a dramatic fall down here in April and that was when we installed a new author and now they're sort of recovering, we can say, "Oh, yeah, you know what? That takes a little while for a new blog author to kind of come up to speed. We're going to give them time," or, "Hey, we should interject here. We need to jump in and try and fix whatever is going on."

3. When they're benchmarked versus relevant industry competitors

Third and final useful case is when you benchmark versus truly relevant industry competitors. So if you have a direct competitor, very similar focus to you, product-focused in this case with a homepage and then some content sections and then a very focused product checkout, you could look at you versus them and their homepage and your homepage.

If you could get the data from a source like SimilarWeb or Jumpshot, if there's enough clickstream level data, or some savvy industry surveys that collect this information, and you see that you're significantly higher, you might then take a look at what are they doing that we're not doing. Maybe we should use them when we do our user research and say, "Hey, what's compelling to you about this that maybe is missing here?"

Otherwise, a lot of the time people will take direct competitors and say, "Hey, let's look at what our competition is doing and we'll consider that best practice." But if you haven't looked at how they're performing, how people are getting through, whether they're engaging, whether they're spending time on that site, whether they're making it through their different pages, you don't know if they actually are best practices or whether you're about to follow a laggard's example and potentially hurt yourself.

So definitely a complex topic, definitely many, many different things that go into the uses of these metrics, and there are some bad and good ways to use them. I agree with Sayf and with Wil, but I think there are also some great ways to apply them. I would love to hear from you if you've got examples of those down in the comments. We'll see you again next week for another edition of Whiteboard Friday. Take care.

Even prior to making changes, I like to compare these metrics between different products or sections, as it often helps finding problems we didn't know exist.

Then, it's very useful to compare between different user segments. Some examples are: New vs returning users, different countries, Android vs iOS behavior, traffic channels, and of course different conversion points. If users who do X are spending more time on your site than users who don't, it's something to investigate. Perhaps you should find a way to push more users into that direction.

You've mentioned SimilarWeb, and one thing SimilarWeb does very well is looking at websites from a single country perspective. So we can not only compare our own websites to direct competitors (Bounce Rate, PPV, Time), but also see how these metrics change between the different countries. Very useful if you have users from multiple countries.

Last, one additional metric I'd like to suggest (even though it's not a default GA metric but a calculated metric), is visits per user. Of course it's more relevant to some sites, but still, it's very important to see what's your average return rate, and keep an eye on it over time. Mainly after changes.

All metrics should first have a hypothesis. The hypothesis should explain why the metric is useful in the context of the goal you are wanting to achieve. Clients often want the single metric because it is easy to understand and therefore easy to criticise or praise your efforts.

Another metric example is Keyword ranking. We had a client who was focussed on a single keyword and always wanted to be number 1 ranked for this keyword (I am sure you have all been here). It was the only metric that mattered and we were judged on that alone. Now...He was right it was an important metric and it did drive a lot of traffic but it was not the correct metric when measuring the success of blog articles or the work we were doing on content in other areas (i do accept the indirect benefits thought). Over time as the industry got more competitive it was harder to maintain a number one position and he did lose the number 1 spot but still ranking high. However his traffic and conversion was increasing because other keywords were working better for him. We roughly estimated that a maximum of 26% of non-branded traffic was from that single keyword but that left 74% so was that really the best metric???

In this case the individual ranking was a general barometer of site competitiveness but because it was a generic keyword and in this sepecific industry customers always shopped around he just needed to be on the first page not always number 1. This meant that the expected conversion rate would be lower. Where he was actually winning was elsehere in the SERPs where he was the only one appearing through good content. This lead to better conversion rates on easier keywords.

Interestingly this example is from 6 years ago but still holds truth today.

Every Metric is interesting/important if and only if it has its context.

totally right. Bounce rate, time on site, pages per visit... should be always seen like statistics to improve so you can get more conversion, taking those visitors to the right place and with desire of buying your product or service. Or, also can be seen as statistics to improve your SEO, because they are some of the most important factors for Google in this years.

There is something that you didn’t touch and it is very relevant for this discussion and it is “adjusted bounce rate”. Let’s say you have a one page website. Then you will likely see a close to 100% bounce rate un GA because of the definition of it.

In my opinion it is very important to manually adjust that bounce rate so you can see the reality. In the previous example I would add an event to the scroll depth for instance to rule out of the bounce rate metric all the deep scrolled page views.

I think that from the highest level these can be looked at as great metrics but not as the single factor in measuring success. When I look at the time on a page or even the bounce rate I go into what has changed on that page, where it is at in the common path of a typical user, and how they got there. I think that Rand did a spot on job for pointing out when to use these metrics and why to use them but also when not to. I think that with the approach of polishing up the existing content and features of a site this can come in so handy as you can see if your changes are affecting these particular metrics.

Thank you so much for sharing this information, as digital marketers we, a lot many times face this problem to know when all these parameters are actually useful and when they are not.Be it the bounce rate, or the pages visited at a time or be it the time spent on the website, all these factors are very important for the On Page SEO perspective, so thanks a ton for elaborating about all this on this platform.

You made a lot of great points, but I'd like to hear your opinion on Kaushik's See-Think-Do article. Kaushik makes a point that all metrics have a time and a place - including conversions. So depending on the message and target audience, do you think that there are instances where bounce rate, PPV, and time on site can be more important than conversions?

You also mention how clicks from social channels will naturally have high bounce rates and low PPVs & site time. While these metrics will likely be worse overall through social sources compared to the SERP, do you think these metrics can be useful for measuring the success of clicks from social channels where the message has a compelling on-site goal, and the targeting is very complimentary to this message and goal. In other words, do you think these metrics suck at measuring social/display performance regardless of the message and targeting?

Bounce rate and pages per visit are critically important for those of us who publish sites with advertising or who have clients doing the same.

A site with 3 ad positions and 2 pages per visit has 6 ad impressions per visit. A site with 3 ad positions and 3 pages per visit has 9 ad impressions or 50% more. So just adding 1 page per visit can have a big impact on revenue.

That 50% more translates into a hefty dose of ad inventory for selling directly to advertisers or filling with ad networks. It really pays off for the site publisher who focuses on pages per visit in a site channel with high RPMs.

Great post Rand! It is important that marketers understand the bounce rates and that they are not to be taken out of context. Home pages vs blogs vs contact pages are not supposed to have the same engagement times. If I had a dollar for everytime I heard someone blindly look at a bounce rate and comment about whether it is good or bad.... Thanks for yet another great lesson!

Hi Rand, I also hold this opinion for long. The data for bounce rate, time on site, pages per visit etc are not essentially the complete picture but they are also indicators and can vary based on lot of factors. The art is to use them to have analytical advantage to make SEO decision.

Hello Rand, from a long time you become inspiration for many people. In this blog the way you have driven out bounce rate and its importance , it is incredible. I wish you a very best luck and keep inspiring others.

On the internet we can find lots of information but in the whole thing existence of the reality is very few, so this the site i found which is really helped me a lot. thank you so much for sharing nice thing.

I wonder if some website got no content? or just services, they probably got high bounce rate. Unless they have video marketing video, or a list that something to check out. Anyway, site traffic our bounce rate can be easily manipulated if you know what you're doing.

Never anything outside the scope of thorough Rand! I'm a big fan of the Advanced image SEO metrics you did a little while back. I did a field study on the social signal and embed aspects of it in a battle of augmenting a news article for a friend of mine that needs reputation management assistance.

I ended up making a second infographic with the 16:9 ratio of a Mona Lisa variance, but this was the first one inspired by your article :-) Rand Fishkin Inspired Infograpic by Sean Gugerty https://i.imgur.com/1bCoCnR.jpg

Hey Rand, thanks for the helpful article! We have a heated Google Analytics debate happening in my office and I was wondering if you could help us end it once and for all:

Is bounce rate an important metric to track and optimize? And more importantly, does it affect a website's SERP ranking?

We write a lot of in-depth content that is helpful for people, including those outside of our ideal customer criteria, so many users visit our blog, get the info they need, and then bounce. We have implemented an adjusted bounce rate (thanks to the help of one of your articles!) that brought it down to 5%, but we're not sure if the "real" bounce rate that's above 90% still has impact on Google.

Any help or recommended resources would be much appreciated in my quest to restore the marketing peace in our office. :)

as always very good post, but I disagree about one of the comments as sometimes bounce rate from search should not be low as if you are answering consumers question in just that page is highly likely that your bounce rate will be bad but that is a good indication for that page as you are been relevant to them.

Different visitors, different intent! Meaning if I show up on a page with a question in mind like, how many cities is there in the UK? I don't need to spend an hour on the page if the article is called " Discover the 1306 cities which make up the UK" If we are talking about an online store with 100 + products and the visitor stays 5 seconds, then this bounce should be investigated.

I think these things are much like everything in the SEO world, easy to manipulate for vanity's sake, but only useful when used in the right way.

To me these just play a part in your overall picture and you have to aim for your own version of 'good' that matches your situation - as with everything else, if its natural and organic, you're probably on the right track.

Hello, if the duration time on our website of our potential clients is medium-level what would be the advantages or disadvantages? For instance I am a hair specialist and want to access more potential customers for my company's web page and keep them longer on my page.

Not necessarily, it depends on the type of website you have, your target audience, the product or services on the site etc. For certain sites the opposite (i.e. high bounce rate and less pageviews per visit) is also a good thing.

Sure I will try to give an example. I have a page that has a chart of today's digital currency values. If some one is looking for what is today's value of X currency they find the value and bounce. I don't lose sleep over that. Now what I do pay attention to is the return visits. That term is not as important as a phrase like "where to buy currency X"? If that was a landing page to buy X it and it had a high bounce rate I would look at the different page elements.

As far as negative signal for search engines, I think the time would be better spent on other parts of the algo. Just my opinion.

Hello Rand! Very good post as always. But I have a question, I've seen the conversion funnel for a web page. But what about a blog? because in a blog people only enter through the keywords. Would the same scheme work? A greeting!!

Hi, It was a great blog post. I am a big fan sir and really follow you on you tube as well. I can just say that you are doing a great work. And as said being a beginner I really have got to learn many new things.